ACI learns to behave the same way as examples, so it can also learn ethics from examples. For example, if behaviors like “getting into a very cold environment” is excluded from all the examples, either by natural selection or artificial selection, an ACI agent can learn ethics like “always getting away from cold”, and use it in the future. If you want to achieve new ethics, you have to either induce from the old ones or learn from selection in something like “supervised stages”.
You didn’t respond to the critical part of my comment: “However, after removing ethics “from the outside”, ACI is left without an adequate replacement. I. e., this is an agent devoid of ethics as a cognitive discipline, which appears to be intimately related to foresight. ACI lacks constructive foresight, too, it always “looks back”, which warranted periodic “supervised learning” stages that seem like a patch-up. This doesn’t appear scalable, too.”
Let me try to rephrase: ACI appears fundamentally inductive, but inductivism doesn’t appear to be a philosophy of science that really leads to general intelligence. A general intelligence should adopt some form of constructivism (note that in my “decomposition” of the “faculties” of general intelligence, based on Active Inference, in the comment above: namely, epistemology, rationality, and ethics, -- are all deeply intertwined, and “ethics” is really about any foresight and normativity, including constructivism). AIXI could be general intelligence because the constructive, normative aspect of intelligence is “assumed away” to the external entity that assigns rewards to different outcomes; with ACI, you basically still assume this aspect of intelligence away, relying on the “caretaker” that will decide what, when and how to teach the ACI. If it’s some other AI that does it, how does that AI know? So, there is an infinite regress, and ACI couldn’t be a universal model of general intelligence.
Also, cf. Safron (2022) discussion of FEP/Active Inference and AIXI.
A few corrections about your reading of Active Inference:
ACI does not divide the learning process into “information gain” and “pragmatic value learning”
First, Active Inference doesn’t really “divide” them such, it’s one of the decompositions of EFE (the other is into ambiguity and risk). Second, it’s just “pragmatic value” here, not “pragmatic value learning”.
In the active inference model, both information gain and action are considered as “minimizing the discrepancy between our model and our world through perception and action”.
Information gain is not coupled/contraposed with action. Action is only contraposed with perception. Perception != information gain. Perception is tuned to minimise VFE (rather than EFE); VFE = complexity + accuracy, but information gain doesn’t feature in VFE.
I think I have already responded to that part. Who is the “caretaker that will decide what, when and how to teach the ACI”? The answer is natural selection or artificial selection, which work like filters. AIXI’s “constructive, normative aspect of intelligence is ‘assumed away’ to the external entity that assigns rewards to different outcomes”, while ACI’s constructive, normative aspect of intelligence is also assumed away to the environment that have determined which behavior was OK and which behavior would get a possible ancestor out of the gene pool. Since the the reward circuit of natural intelligence is shaped by natural selection, ACI is also eligible to be a universal model of intelligence.
Thank you for your correction about Active Inference reading, I will read more then respond to that.
You didn’t respond to the critical part of my comment: “However, after removing ethics “from the outside”, ACI is left without an adequate replacement. I. e., this is an agent devoid of ethics as a cognitive discipline, which appears to be intimately related to foresight. ACI lacks constructive foresight, too, it always “looks back”, which warranted periodic “supervised learning” stages that seem like a patch-up. This doesn’t appear scalable, too.”
Let me try to rephrase: ACI appears fundamentally inductive, but inductivism doesn’t appear to be a philosophy of science that really leads to general intelligence. A general intelligence should adopt some form of constructivism (note that in my “decomposition” of the “faculties” of general intelligence, based on Active Inference, in the comment above: namely, epistemology, rationality, and ethics, -- are all deeply intertwined, and “ethics” is really about any foresight and normativity, including constructivism). AIXI could be general intelligence because the constructive, normative aspect of intelligence is “assumed away” to the external entity that assigns rewards to different outcomes; with ACI, you basically still assume this aspect of intelligence away, relying on the “caretaker” that will decide what, when and how to teach the ACI. If it’s some other AI that does it, how does that AI know? So, there is an infinite regress, and ACI couldn’t be a universal model of general intelligence.
Also, cf. Safron (2022) discussion of FEP/Active Inference and AIXI.
A few corrections about your reading of Active Inference:
First, Active Inference doesn’t really “divide” them such, it’s one of the decompositions of EFE (the other is into ambiguity and risk). Second, it’s just “pragmatic value” here, not “pragmatic value learning”.
Information gain is not coupled/contraposed with action. Action is only contraposed with perception. Perception != information gain. Perception is tuned to minimise VFE (rather than EFE); VFE = complexity + accuracy, but information gain doesn’t feature in VFE.
I think I have already responded to that part. Who is the “caretaker that will decide what, when and how to teach the ACI”? The answer is natural selection or artificial selection, which work like filters. AIXI’s “constructive, normative aspect of intelligence is ‘assumed away’ to the external entity that assigns rewards to different outcomes”, while ACI’s constructive, normative aspect of intelligence is also assumed away to the environment that have determined which behavior was OK and which behavior would get a possible ancestor out of the gene pool. Since the the reward circuit of natural intelligence is shaped by natural selection, ACI is also eligible to be a universal model of intelligence.
Thank you for your correction about Active Inference reading, I will read more then respond to that.